class_docstr: Create PNG plots of samples from a GAN model.
  
  Arguments:
      filename (string): Filename prefix for output PNGs.
      hw (int): Height and width of the images.
      nchan (int): number of channels.
      num_saples (int): how many samples to show from traning and generated data.
      sym_range (bool): pixel value [-1, 1] or [0, 1].
      padding (int): number of pixels to pad in output images.
      plot_width (int): width of output images.
      plot_height (int): height of output images.
      dpi (float): dots per inch.
      font_size (int): font size of labels.
      epoch_freq (int): number of epochs per plotting callback.
code: def __init__(
      self,
      filename,
      hw=28,
      nchan=1,
      num_samples=16,
      sym_range=False,
      padding=2,
      plot_width=1200,
      plot_height=600,
      dpi=60.0,
      font_size=10,
      epoch_freq=1,
  ):
      super(GANPlotCallback, self).__init__(epoch_freq=epoch_freq)
      self.filename = filename
      self.hw = hw
      self.nchan = nchan
      self.num_samples = num_samples
      self.padding = padding
      self.sym_range = sym_range
      self.plot_width = plot_width
      self.plot_height = plot_height
      self.dpi = dpi
      self.font_size = font_size
  
file_path: neon/neon/callbacks/plotting_callbacks.py
imports: from __future__ import division
  import logging
  import numpy
  from PIL import Image
  from neon.callbacks.callbacks import Callback
label_desc: Use image node_id 1 to create a new GANPlotCallback object from inherited base classes: Callback with example: obj = GANPlotCallback(filename, hw, nchan, num_samples, sym_range, padding, plot_width, plot_height, dpi, font_size, epoch_freq)